IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i1p376-d304638.html
   My bibliography  Save this article

Understanding Better the Influential Factors of Commuters’ Multi-Day Travel Behavior: Evidence from Shanghai, China

Author

Listed:
  • Xiaoning Liu

    (School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
    China Institute of Urban Governance, Shanghai Jiao Tong University, Shanghai 200240, China)

  • Linjie Gao

    (School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
    China Institute of Urban Governance, Shanghai Jiao Tong University, Shanghai 200240, China)

  • Anning Ni

    (School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
    China Institute of Urban Governance, Shanghai Jiao Tong University, Shanghai 200240, China)

  • Nan Ye

    (School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
    China Institute of Urban Governance, Shanghai Jiao Tong University, Shanghai 200240, China)

Abstract

Alleviating traffic congestion and developing sustainable transportation systems in a city can be assisted by promoting environmentally friendly transportation modes such as walking, cycling, and public transport. Strategies for promoting these desirable transportation modes can be identified based on a sound understanding of how commuters choose travel modes. In this study, multi-day commuting travel mode data was used to explore factors that influenced commute mode choice. A multinomial logit model and a binary logit model were proposed to study commuter travel behavior. The results showed the following. (1) Age, gender, and marriage indirectly influence the commute mode choice; (2) The cost of travel mode has little effect on commute mode choice; (3) The probability of commute mode change mainly influences the car mode choice; (4) The number of transfer times and the distance to the nearest public transport stations are main factors that restrict commuters from choosing public transport; (5) The number of bicycles in the family and commute distance are main factors that restrict commuters from choosing cycling for commuting. Based on these findings, several potential measures are demonstrated to policymakers and transportation planners to alleviate traffic congestion and develop sustainable transportation systems.

Suggested Citation

  • Xiaoning Liu & Linjie Gao & Anning Ni & Nan Ye, 2020. "Understanding Better the Influential Factors of Commuters’ Multi-Day Travel Behavior: Evidence from Shanghai, China," Sustainability, MDPI, vol. 12(1), pages 1-13, January.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:1:p:376-:d:304638
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/1/376/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/1/376/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chakrabarti, Sandip, 2017. "How can public transit get people out of their cars? An analysis of transit mode choice for commute trips in Los Angeles," Transport Policy, Elsevier, vol. 54(C), pages 80-89.
    2. Kay Axhausen & Andrea Zimmermann & Stefan Schönfelder & Guido Rindsfüser & Thomas Haupt, 2002. "Observing the rhythms of daily life: A six-week travel diary," Transportation, Springer, vol. 29(2), pages 95-124, May.
    3. Simone Borghesi & Chiara Calastri & Giorgio Fagiolo, 2014. "How do people choose their commuting mode? An evolutionary approach to transport choices," LEM Papers Series 2014/15, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    4. Astrid De Witte & Joachim Hollevoet & Frédéric Dobruszkes & Michel Hubert & Cathy Macharis, 2013. "Linking modal choice to motility: a comprehensive review," ULB Institutional Repository 2013/138176, ULB -- Universite Libre de Bruxelles.
    5. Heinen, Eva & Chatterjee, Kiron, 2015. "The same mode again? An exploration of mode choice variability in Great Britain using the National Travel Survey," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 266-282.
    6. Peng Jing & Mengxuan Zhao & Meiling He & Long Chen, 2018. "Travel Mode and Travel Route Choice Behavior Based on Random Regret Minimization: A Systematic Review," Sustainability, MDPI, vol. 10(4), pages 1-20, April.
    7. De Witte, Astrid & Hollevoet, Joachim & Dobruszkes, Frédéric & Hubert, Michel & Macharis, Cathy, 2013. "Linking modal choice to motility: A comprehensive review," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 329-341.
    8. Javier Asensio, 2002. "Transport Mode Choice by Commuters to Barcelona's CBD," Urban Studies, Urban Studies Journal Limited, vol. 39(10), pages 1881-1895, September.
    9. Hasnine, Md Sami & Lin, TianYang & Weiss, Adam & Habib, Khandker Nurul, 2018. "Determinants of travel mode choices of post-secondary students in a large metropolitan area: The case of the city of Toronto," Journal of Transport Geography, Elsevier, vol. 70(C), pages 161-171.
    10. Arbués, Pelayo & Baños, José F. & Mayor, Matías & Suárez, Patricia, 2016. "Determinants of ground transport modal choice in long-distance trips in Spain," Transportation Research Part A: Policy and Practice, Elsevier, vol. 84(C), pages 131-143.
    11. Robert Schlich & Kay Axhausen, 2003. "Habitual travel behaviour: Evidence from a six-week travel diary," Transportation, Springer, vol. 30(1), pages 13-36, February.
    12. Dargay, Joyce, 2007. "The effect of prices and income on car travel in the UK," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(10), pages 949-960, December.
    13. Junyi Shen, 2009. "Latent class model or mixed logit model? A comparison by transport mode choice data," Applied Economics, Taylor & Francis Journals, vol. 41(22), pages 2915-2924.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Maosheng Li & Hui Xie & Panpan Shu, 2021. "Study on the Impact of Traffic Accidents in Key Areas of Rural Roads," Sustainability, MDPI, vol. 13(14), pages 1-17, July.
    2. Rocio de la Torre & Canan G. Corlu & Javier Faulin & Bhakti S. Onggo & Angel A. Juan, 2021. "Simulation, Optimization, and Machine Learning in Sustainable Transportation Systems: Models and Applications," Sustainability, MDPI, vol. 13(3), pages 1-21, February.
    3. Muhammad Ashraf Javid & Nazam Ali & Tiziana Campisi & Giovanni Tesoriere & Krisada Chaiyasarn, 2022. "Influence of Social Constraints, Mobility Incentives, and Restrictions on Commuters’ Behavioral Intentions and Moral Obligation towards the Metro-Bus Service in Lahore," Sustainability, MDPI, vol. 14(5), pages 1-19, February.
    4. Jingzhao Wang & Jincheng Yan & Keyuan Ding & Qian Li & Yehao Liu & Xueliang Liu & Ran Peng, 2022. "A Reflection on the Response to Sudden-Onset Disasters in the Post-Pandemic Era: A Graded Assessment of Urban Transportation Resilience Taking Wuhan, China as an Example," Sustainability, MDPI, vol. 14(17), pages 1-20, September.
    5. Alejandro Sánchez-Atondo & Leonel García & Julio Calderón-Ramírez & José Manuel Gutiérrez-Moreno & Alejandro Mungaray-Moctezuma, 2020. "Understanding Public Transport Ridership in Developing Countries to Promote Sustainable Urban Mobility: A Case Study of Mexicali, Mexico," Sustainability, MDPI, vol. 12(8), pages 1-21, April.
    6. Woo Jang & Fei Yuan & Jose Javier Lopez, 2021. "Investigating Sustainable Commuting Patterns by Socio-Economic Factors," Sustainability, MDPI, vol. 13(4), pages 1-14, February.
    7. Zijia Wang & Hao Tang & Wenjuan Wang & Yang Xi, 2020. "The Pattern of Non-Roundtrip Travel on Urban Rail and Its Application in Transit Improvement," Sustainability, MDPI, vol. 12(9), pages 1-16, April.
    8. Sun, Shichao & Yao, Yukun & Xu, Lingyu & He, Xuan & Duan, Zhengyu, 2022. "The use of E-moped increases commute satisfaction and subjective well-being: Evidence from Shanghai, China," Transport Policy, Elsevier, vol. 117(C), pages 60-73.
    9. Edgar Gutierrez-Franco & Christopher Mejia-Argueta & Luis Rabelo, 2021. "Data-Driven Methodology to Support Long-Lasting Logistics and Decision Making for Urban Last-Mile Operations," Sustainability, MDPI, vol. 13(11), pages 1-33, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ha, Jaehyun & Lee, Sugie & Ko, Joonho, 2020. "Unraveling the impact of travel time, cost, and transit burdens on commute mode choice for different income and age groups," Transportation Research Part A: Policy and Practice, Elsevier, vol. 141(C), pages 147-166.
    2. Milad Mehdizadeh & Alireza Ermagun, 2020. "“I’ll never stop driving my child to school”: on multimodal and monomodal car users," Transportation, Springer, vol. 47(3), pages 1071-1102, June.
    3. Thomas, Tom & La Paix Puello, Lissy & Geurs, Karst, 2019. "Intrapersonal mode choice variation: Evidence from a four-week smartphone-based travel survey in the Netherlands," Journal of Transport Geography, Elsevier, vol. 76(C), pages 287-300.
    4. Obregón-Biosca, Saúl A., 2022. "Choice of transport in urban and periurban zones in metropolitan area," Journal of Transport Geography, Elsevier, vol. 100(C).
    5. Ko, Joonho & Lee, Sugie & Byun, Miree, 2019. "Exploring factors associated with commute mode choice: An application of city-level general social survey data," Transport Policy, Elsevier, vol. 75(C), pages 36-46.
    6. Charreire, H. & Roda, C. & Feuillet, T. & Piombini, A. & Bardos, H. & Rutter, H. & Compernolle, S. & Mackenbach, J.D. & Lakerveld, J. & Oppert, J.M., 2021. "Walking, cycling, and public transport for commuting and non-commuting travels across 5 European urban regions: Modal choice correlates and motivations," Journal of Transport Geography, Elsevier, vol. 96(C).
    7. Crawford, F. & Watling, D.P. & Connors, R.D., 2018. "Identifying road user classes based on repeated trip behaviour using Bluetooth data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 113(C), pages 55-74.
    8. Wójcik Szymon, 2019. "The determinants of travel mode choice: the case of Łódź, Poland," Bulletin of Geography. Socio-economic Series, Sciendo, vol. 44(44), pages 93-101, June.
    9. Bouscasse, Hélène & de Lapparent, Matthieu, 2019. "Perceived comfort and values of travel time savings in the Rhône-Alpes Region," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 370-387.
    10. Heinen, Eva & Chatterjee, Kiron, 2015. "The same mode again? An exploration of mode choice variability in Great Britain using the National Travel Survey," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 266-282.
    11. Mathieu Lambotte & Sandrine Mathy & Anna Risch & Carole Treibich, 2022. "Spreading active transportation: peer effects and key players in the workplace," Post-Print hal-03702684, HAL.
    12. Sanjay Gupta & Kushagra Sinha, 2022. "Assessing the Factors Impacting Transport Usage of Mobility App Users in the National Capital Territory of Delhi, India," Sustainability, MDPI, vol. 14(21), pages 1-20, October.
    13. Chaloupka, Christine & Kölbl, Robert & Loibl, Wolfgang & Molitor, Romain & Nentwich, Michael & Peer, Stefanie & Risser, Ralf & Sammer, Gerd & Schützhofer, Bettina & Seibt, Claus, 2015. "Nachhaltige Mobilität aus sozioökonomischer Perspektive – Diskussionspapier der Arbeitsgruppe "Sozioökonomische Aspekte" der ÖAW-Kommission "Nachhaltige Mobilität" (ITA-manu," ITA manu:scripts 15_02, Institute of Technology Assessment (ITA).
    14. Zhihao Duan & Jinliang Xu & Han Ru & Yaping Dong & Xingliang Liu, 2019. "Analysis of Emergency Evacuation Modal Choice Behavior with Spatial Indicators: Case Study in Xi’an, China," Sustainability, MDPI, vol. 11(24), pages 1-10, December.
    15. Minnen, Joeri & Glorieux, Ignace & van Tienoven, Theun Pieter, 2015. "Transportation habits: Evidence from time diary data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 76(C), pages 25-37.
    16. Maurici Ruiz-Pérez & Joana Maria Seguí-Pons, 2020. "Transport Mode Choice for Residents in a Tourist Destination: The Long Road to Sustainability (the Case of Mallorca, Spain)," Sustainability, MDPI, vol. 12(22), pages 1-31, November.
    17. Laureti, Tiziana & Montero, José-María & Fernández-Avilés, Gema, 2014. "A local scale analysis on influencing factors of NOx emissions: Evidence from the Community of Madrid, Spain," Energy Policy, Elsevier, vol. 74(C), pages 557-568.
    18. Bouscasse, H., 2018. "Integrated choice and latent variable models: A literature review on mode choice," Working Papers 2018-07, Grenoble Applied Economics Laboratory (GAEL).
    19. Charles Raux & Tai-Yu Ma & Eric Cornelis, 2011. "Variability versus stability in daily travel and activity behaviour. The case of a one week travel diary," Working Papers halshs-00612610, HAL.
    20. Chakrabarti, Sandip, 2022. "Passively wait for gridlock, or proactively invest in service? Strategies to promote car-to-transit switches among aspirational urbanites in rapidly developing contexts," Transport Policy, Elsevier, vol. 115(C), pages 251-261.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:12:y:2020:i:1:p:376-:d:304638. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.